Towards recommender systems based on a fuzzy preference aggregation

DOI

10.2991/eusflat.2013.21How to use a DOI?

Keywords

Recommender system fuzzy preferences preference graph fuzzy sets

Abstract

An approach to deal with user preference relations, instead of absolute ratings, in recommender systems is discussed. User’s preferences are then ratings expressed qualitatively by using linguistic terms. This is a suitable technique when preferences are imprecise and vague. On the other hand, to avoid that the overall item rating may hide the users’ preferences heterogeneity and mislead the system when predicting the items that users are interested in, multi-criteria ratings are used as well. User’s items ratings are represented through a preference graph which highlight better items relationships. Similarity between users is performed on the basis of the similarity of their preference relations which can better capture similar users’ ratings patterns. As it will be shown, the approach enhances the classical recommender system precision thanks to the graphs used for prediction which are more informative and reflect user’s initial ratings relations in a better way.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Samia Boulkrinat
AU  - Allel Hadjali
AU  - Aicha Mokhtari
PY  - 2013/08
DA  - 2013/08
TI  - Towards recommender systems based on a fuzzy preference aggregation
BT  - Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
PB  - Atlantis Press
SP  - 146
EP  - 153
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2013.21
DO  - 10.2991/eusflat.2013.21
ID  - Boulkrinat2013/08
ER  -